Biomarkers Predictive of Response to Thiopurine Therapy in Inflammatory Bowel Disease

White Blood Cell Counts and Future Relapse in Ulcerative Colitis under Low-Dose Thiopurine Treatment in Real-World Practice: A 3-Year Japanese Multi-Center Retrospective Cohort Study

Introduction

Whether white blood cell (WBC) counts are predictors for the effectiveness of thiopurine treatment in ulcerative colitis (UC) has been inconclusive in previous studies with small sample sizes. We investigated the association between WBC counts and future relapses in UC patients in a large-scale multi-center study.

Methods

This retrospective cohort study enrolled a total of 723 UC patients in remission from 33 hospitals and followed up for 3 years. Relapse was defined as a need for treatment intensification. The risk of relapse was compared among patients with the baseline WBC counts <3,000/µL (N = 31), 3,000-4,000/µL (N = 167), 4,000-5,000/µL (N = 241), and ≥5,000/µL (N = 284) using a Cox regression model analysis. Moreover, exploratory analyses were conducted to identify other factors predicting relapse.

Results

During a median follow-up period of 1,095 (interquartile range, 1,032-1,119) days, relapse occurred in 17.2% (125/723). In a crude analysis, WBC counts were not associated with relapse; hazard ratios (HRs) (95% confidence interval [CI]) were 1.50 (0.74-3.06), 1.02 (0.66-1.59), and 0.67 (0.43-1.05) in WBC <3,000/µL, 3,000-4,000/µL, and 4,000-5,000/µL groups, respectively (WBC ≥5,000/µL group, as reference). Multivariable-adjusted analyses showed similar results; HRs (95% CI) were 1.21 (0.59-2.49), 1.08 (0.69-1.69), and 0.69 (0.44-1.07), in <3,000/µL, 3,000-4,000/µL, and 4,000-5,000/µL groups, respectively. In the exploratory analyses, thiopurine use <1 year and a mean corpuscular volume <90 fL were predictors for relapse.

Discussion/Conclusion

WBC counts were not predictors for future relapses in patients with UC treated with thiopurine as a maintenance therapy.

Identifying predictors of clinical outcomes using the projection-predictive feature selection-a proof of concept on the example of Crohn's disease

Objectives

Several clinical disease activity indices (DAIs) have been developed to noninvasively assess mucosal healing in pediatric Crohn's disease (CD). However, their clinical application can be complex. Therefore, we present a new way to identify the most informative biomarkers for mucosal inflammation from current markers in use and, based on this, how to obtain an easy-to-use DAI for clinical practice. A further aim of our proof-of-concept study is to demonstrate how the performance of such a new DAI can be compared to that of existing DAIs.

Methods

The data of two independent study cohorts, with 167 visits from 109 children and adolescents with CD, were evaluated retrospectively. A variable selection based on a Bayesian ordinal regression model was applied to select clinical or standard laboratory parameters as predictors, using an endoscopic outcome. The predictive performance of the resulting model was compared to that of existing pediatric DAIs.

Results

With our proof-of-concept dataset, the resulting model included C-reactive protein (CRP) and fecal calprotectin (FC) as predictors. In general, our model performed better than the existing DAIs. To show how our Bayesian approach can be applied in practice, we developed a web application for predicting disease activity for a new CD patient or visit.

Conclusions

Our work serves as a proof-of-concept, showing that the statistical methods used here can identify biomarkers relevant for the prediction of a clinical outcome. In our case, a small number of biomarkers is sufficient, which, together with the web interface, facilitates the clinical application. However, the retrospective nature of our study, the rather small amount of data, and the lack of an external validation cohort do not allow us to consider our results as the establishment of a novel DAI for pediatric CD. This needs to be done with the help of a prospective study with more data and an external validation cohort in the future.

Effects of Pine Pollen Polysaccharides and Sulfated Polysaccharides on Ulcerative Colitis and Gut Flora in Mice

Polysaccharides are important biological macromolecules in all organisms, and have recently been studied as therapeutic agents for ulcerative colitis (UC). However, the effects of Pinus yunnanensis pollen polysaccharides on ulcerative colitis remains unknown. In this study, dextran sodium sulfate (DSS) was used to induce the UC model to investigate the effects of Pinus yunnanensis pollen polysaccharides (PPM60) and sulfated polysaccharides (SPPM60) on UC. We evaluated the improvement of polysaccharides on UC by analyzing the levels of intestinal cytokines, serum metabolites and metabolic pathways, intestinal flora species diversity, and beneficial and harmful bacteria. The results show that purified PPM60 and its sulfated form SPPM60 effectively alleviated the disease progression of weight loss, colon shortening and intestinal injury in UC mice. On the intestinal immunity level, PPM60 and SPPM60 increased the levels of anti-inflammatory cytokines (IL-2, IL-10, and IL-13) and decreased the levels of proinflammatory cytokines (IL-1β, IL-6, and TNF-α). On the serum metabolism level, PPM60 and SPPM60 mainly regulated the abnormal serum metabolism of UC mice by regulating the energy-related and lipid-related metabolism pathways, respectively. On the intestinal flora level, PPM60 and SPPM60 reduced the abundance of harmful bacteria (such as Akkermansia and Aerococcus) and induced the abundance of beneficial bacteria (such as lactobacillus). In summary, this study is the first to evaluate the effects of PPM60 and SPPM60 on UC from the joint perspectives of intestinal immunity, serum metabolomics, and intestinal flora, which may provide an experimental basis for plant polysaccharides as an adjuvant clinical treatment of UC.

Challenges in the management of inflammatory bowel disease in sub-Saharan Africa

Inflammatory bowel disease (IBD) is generally considered a disease of high-income countries and is regarded as rare in sub-Saharan Africa. However, this assumption is almost certainly an underestimate, and the high burden of communicable diseases makes IBD in sub-Saharan Africa difficult to detect. Furthermore, some gastrointestinal infections can closely mimic IBD, contributing to delays in diagnosis and complicating therapeutic decision making. Constraints in endoscopic capacity alongside a scarcity of qualified diagnostic pathologists add to the difficulties. Implementing evidence-based guidelines recommended by international societies is challenging, mostly due to high costs and unavailability of medication. However, cost-effective approaches can still be implemented to manage IBD in sub-Saharan Africa as the predominant disease phenotype is mild-to-moderate ulcerative colitis, which often responds to treatment with basic medication. In this Series paper, we summarise the current management of IBD in sub-Saharan Africa and propose how it can be tailored to suit the epidemiological and socioeconomic specificities of the region. We also discuss measures required to address existing challenges, such as educating health-care workers about the diagnosis and management of IBD or improving endoscopic capacity.

Genotype-Guided Prescription of Azathioprine Reduces the Incidence of Adverse Drug Reactions in TPMT Intermediate Metabolizers to a Similar Incidence as Normal Metabolizers

Introduction

Thiopurine drugs are purine nucleoside analogues used for treatment of different immune-related conditions. To date, different studies highlighted the importance of thiopurine methyltransferase (TPMT) genotyping in patients who initiate treatment with thiopurines to make an adequate dose adjustment. We aimed to investigate the influence of TPMT phenotype, concomitant treatments, and demographic characteristics on the incidence of adverse reactions (ADRs) in patients who start treatment with azathioprine (AZA).

Methods

This was an observational and retrospective study. The study population comprised 109 patients who started treatment with AZA following routine TPMT genotyping before June 2019 and who were routinely followed up at Hospital Universitario de La Princesa. The incidence of ADRs and treatment duration were evaluated according to TPMT phenotype.

Results

Forty-five men and 64 women were recruited, with a mean age of 67.6 ± 18.5. The medical specialty with the most requests was dermatology (45.9%) and the most frequent disease for which genotyping was requested was bullous pemphigoid (27.5%). All patients were normal metabolizers (NM), except for eight intermediate metabolizers (IM) (7.3%); no poor metabolizers (PM) were found. The initial azathioprine dose was subtherapeutic in both groups (103.2 ± 45.4 mg in NMs and 75 ± 32.3 mg in IMs), increasing during the first months of treatment, especially in NMs (120.3 ± 41.3 vs. 78.6 ± 30.4 mg in IMs, p = 0.011). Most patients (73.4%) received corticosteroids to keep the disease under control; and for 41.2% of NMs, physicians were able to reduce the dose at 6 months post treatment. No IMs completed 6 months of treatment. Hepatotoxicity, gastric intolerance, and blood disorders were the most common ADRs. The incidence of ADRs in the sample was 28.4% (n = 31) with a similar trend between IMs (37.5%) and NMs (27.8%). Patients undergoing concomitant treatment with allopurinol were associated with a higher incidence of ADRs (n = 4, 100% vs. n = 105, 20%; p = 0.002).

Conclusion

TPMT genotyping before AZA prescription reduces ADR incidence in IMs to a similar level as NMs in the Spanish population. However, it is important to note no IMs completed 6 months of treatment, suggesting that there may be some differences in drug tolerability according to phenotype. In addition, most NMs are treated with subtherapeutic doses, are poorly followed up, and thus suffer avoidable ADRs. Finally, concomitant therapies that inhibit the xanthine oxidase enzyme (XDH), such as allopurinol, predispose to ADRs. Therefore, pharmacogenetic testing should be integrated as an additional clinical tool, in such a way that each patient receives personalized, precision treatment, where all factors influencing drug response are considered.

Cytotoxicity of Thiopurine Drugs in Patients with Inflammatory Bowel Disease

The effectiveness of thiopurine drugs in inflammatory bowel disease (IBD) was confirmed more than a half-century ago. It was proven that these can be essential immunomodulatory medications. Since then, they have been used routinely to maintain remission of Crohn’s disease (CD) and ulcerative colitis (UC). The cytotoxic properties of thiopurines and the numerous adverse effects of the treatment are controversial. However, the research subject of their pharmacology, therapy monitoring, and the search for predictive markers are still very relevant. In this article, we provide an overview of the current knowledge and findings in the field of thiopurines in IBD, focusing on the aspect of their cytotoxicity. Due to thiopurines’ benefits in IBD therapy, it is expected that they will still constitute an essential part of the CD and UC treatment algorithm. More studies are still required on the modulation of the action of thiopurines in combination therapy and their interaction with the gut microbiota.

Current status and future perspectives on the use of therapeutic drug monitoring of thiopurine metabolites in patients with inflammatory bowel disease

INTRODUCTION

Despite new treatment options for inflammatory bowel disease (IBD), conventional thiopurines remain a common treatment option for maintaining remission, particularly in non-Westernized countries. Therapeutic drug monitoring (TDM) is advised in standard care for optimizing therapy strategies to improve effectiveness, reveal nonadherence and reduce toxicity. Still, the rationale of TDM is debated.

AREAS COVERED

Key insights on TDM of thiopurine metabolites are discussed. The pharmacology of thiopurines is described, emphasizing the interindividual differences in pharmacogenetics, pharmacokinetics and pharmacodynamics. Pharmacological differences between conventional thiopurines and tioguanine are outlined. Finally, several optimization strategies for thiopurine therapy in IBD are discussed.

EXPERT OPINION

TDM has been a useful, but limited, tool to individualize thiopurine therapy. Pharmacokinetic data on the active thiopurine metabolites, derived from measurements in erythrocytes, associated with clinical response only partially predict effectiveness and toxicity. An additional pharmacodynamic marker, such as Rac1/pSTAT3 expression in leukocytes, may improve applicability of TDM in the future.

Deep learning vs conventional learning algorithms for clinical prediction in Crohn's disease: A proof-of-concept study

BACKGROUND

Traditional methods of developing predictive models in inflammatory bowel diseases (IBD) rely on using statistical regression approaches to deriving clinical scores such as the Crohn's disease (CD) activity index. However, traditional approaches are unable to take advantage of more complex data structures such as repeated measurements. Deep learning methods have the potential ability to automatically find and learn complex, hidden relationships between predictive markers and outcomes, but their application to clinical prediction in CD and IBD has not been explored previously.

AIM

To determine and compare the utility of deep learning with conventional algorithms in predicting response to anti-tumor necrosis factor (anti-TNF) therapy in CD.

METHODS

This was a retrospective single-center cohort study of all CD patients who commenced anti-TNF therapy (either adalimumab or infliximab) from January 1, 2010 to December 31, 2015. Remission was defined as a C-reactive protein (CRP) < 5 mg/L at 12 mo after anti-TNF commencement. Three supervised learning algorithms were compared: (1) A conventional statistical learning algorithm using multivariable logistic regression on baseline data only; (2) A deep learning algorithm using a feed-forward artificial neural network on baseline data only; and (3) A deep learning algorithm using a recurrent neural network on repeated data. Predictive performance was assessed using area under the receiver operator characteristic curve (AUC) after 10× repeated 5-fold cross-validation.

RESULTS

A total of 146 patients were included (median age 36 years, 48% male). Concomitant therapy at anti-TNF commencement included thiopurines (68%), methotrexate (18%), corticosteroids (44%) and aminosalicylates (33%). After 12 mo, 64% had CRP < 5 mg/L. The conventional learning algorithm selected the following baseline variables for the predictive model: Complex disease behavior, albumin, monocytes, lymphocytes, mean corpuscular hemoglobin concentration and gamma-glutamyl transferase, and had a cross-validated AUC of 0.659, 95% confidence interval (CI): 0.562-0.756. A feed-forward artificial neural network using only baseline data demonstrated an AUC of 0.710 (95%CI: 0.622-0.799; P = 0.25 vs conventional). A recurrent neural network using repeated biomarker measurements demonstrated significantly higher AUC compared to the conventional algorithm (0.754, 95%CI: 0.674-0.834; P = 0.036).

CONCLUSION

Deep learning methods are feasible and have the potential for stronger predictive performance compared to conventional model building methods when applied to predicting remission after anti-TNF therapy in CD.

A literature review on large intestinal hyperelastic constitutive modeling

Impacts, traumas and strokes are spontaneously life-threatening, but chronic symptoms strangle patient every day. Colorectal tissue mechanics in such chronic situations not only regulates the physio-psychological well-being of the patient, but also confirms the level of comfort and post-operative clinical outcomes. Numerous uniaxial and multiaxial tensile experiments on healthy and affected samples have evidenced significant differences in tissue mechanical behavior and strong colorectal anisotropy across each layer in thickness direction and along the length. Furthermore, this study reviewed various forms of passive constitutive models for the highly fibrous colorectal tissue ranging from the simplest linearly elastic and the conventional isotropic hyperelastic to the most sophisticated second harmonic generation image based anisotropic mathematical formulation. Under large deformation, the isotropic description of tissue mechanics is unequivocally ineffective which demands a microstructural based tissue definition. Therefore, the information collected in this review paper would present the current state-of-the-art in colorectal biomechanics and profoundly serve as updated computational resources to develop a sophisticated characterization of colorectal tissues.

Biomarkers of Inflammation in Inflammatory Bowel Disease: How Long before Abandoning Single-Marker Approaches?

BACKGROUND

Inflammatory bowel disease (IBD) is a chronically relapsing disease with a continuous need for proactive monitoring to decide appropriate treatments and follow-up strategies. To date, gastrointestinal endoscopy with histologic examination of biopsies and contrast-enhanced imaging are mandatory techniques for the diagnosis and the activity assessment of IBD.

SUMMARY

In recent decades, many research efforts in the IBD field have been placed on finding non-invasive and reliable biomarkers of disease burden that can be easily tested in body fluids without impacting the quality of life of patients. Unfortunately, the ideal biomarker is yet to be discovered and recent studies have investigated the possibility to increase the accuracy of such measurements by combining different markers. In this review, we provide an update about the current knowledge on biomarkers of intestinal inflammation in IBD, focussing on disease diagnosis, correlation with endoscopic findings, and prediction of relapse. We also summarize composite scores of clinical and laboratory markers that have been recently proposed in various scenarios of disease activity. Key Messages: To date, only C-reactive protein and faecal calprotectin can be considered reliable markers of disease activity with demonstrated utility in IBD management. The combination of different parameters has recently shown higher accuracy and might substitute single-marker approaches in the future of research and clinical practice.

Biomarkers of Crohn's Disease to Support the Development of New Therapeutic Interventions

BACKGROUND

Currently, 2 coprimary end points are used by health authorities to determine the effectiveness of therapeutic interventions in patients with Crohn's disease (CD): symptomatic remission (patient-reported outcome assessment) and endoscopic remission (ileocolonoscopy). However, there is lack of accepted biomarkers to facilitate regulatory decision-making in the development of novel therapeutics for the treatment of CD.

METHODS

With support from the Helmsley Charitable Trust, Critical Path Institute formed the Crohn's Disease Biomarkers preconsortium (CDBpC) with members from the pharmaceutical industry, academia, and nonprofit organizations to evaluate the CD biomarker landscape. Biomarkers were evaluated based on biological relevance, availability of biomarker assays, and clinical validation data.

RESULTS

The CDBpC identified the most critical need as pharmacodynamic/response biomarkers to monitor disease activity in response to therapeutic intervention. Fecal calprotectin (FC) and serum C-reactive protein (CRP) were identified as biomarkers ready for the regulatory qualification process. A number of exploratory biomarkers and potential panels of these biomarkers was also identified for additional development. Given the different factors involved in CD and disease progression, a combination of biomarkers, including inflammatory, tissue injury, genetic, and microbiome-associated biomarkers, will likely have the most utility.

CONCLUSIONS

The primary focus of the Inflammatory Bowel Disease Regulatory Science Consortium will be development of exploratory biomarkers and the qualification of FC and CRP for IBD. The Inflammatory Bowel Disease Regulatory Science Consortium, focused on tools to support IBD drug development, will operate in the precompetitive space to share data, biological samples for biomarker testing, and assay information for novel biomarkers.